More Tools to Combat Spam

The war is afoot between spammers and legitimate senders of mass e-mail. They have an ever-increasing number of weapons in the form of algorithms and list management tools. These tools will affect e-mail delivery and reduce the amount of spam that has hijacked the e-mail industry.

As reported from the New Scientist, researchers from IBM and Cornell University developed a new algorithm for detecting spam in e-mails called SMTP Path Analysis. The algorithm works by examining the path information (probably by looking at the Received headers) and detects patterns that are likely to be the route of a spammer. Though the algorithm is not meticulous enough to catch spam on its own efficiently, it works well when combined with content filtering tools.

Engineers at ActivSoftware recently announced their new algorithm called “slow start outbound connection ramping.” This new technology attempts to avoid becoming flagged as spam by automatically monitoring delivery success and failure rates and adjusting simultaneous connections to an e-mail service provider based upon those parameters.

It begins with a very low number of simultaneous connections to any one ESP for any one IP address. It monitors delivery failure to success ratios and slowly ramps up the number of connections to that ESP from that particular IP.

In another recent attempt to help legitimate e-mail senders avoid becoming flagged as spammers, researchers at ActivSoftware, using a bayesian spam filter, sifted more than 200,000 words flowing through their e-mail servers and itemized the 50 or so words most likely to trigger spam filters. The words are organized by their spam to ham ratio, or illegitimate to legitimate email ratio. The team analyzed many factors within this data, but the most compelling was the spam to ham ratios.

Words such as “click” and “here” don’t rank as high because they are used often in legitimate e-mail. Whereas words like “madam,” rarely found in legitimate e-mail yet readily found in spam, had very high ratios. Using this method the team created what it deemed “a superior list of spam words.”

The top 12 words: homeowner, discreet, madam, materially, unclaimed, anticipates, soma, preapproved, unconditionally, beneficiary, refinance, intercourse.

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